Towards correlative super‐resolution fluorescence and electron cryo‐microscopy

Correlative light and electron microscopy (CLEM) has become a powerful tool in life sciences. Particularly cryo‐CLEM, the combination of fluorescence cryo‐microscopy (cryo‐FM) permitting for non‐invasive specific multi‐colour labelling, with electron cryo‐microscopy (cryo‐EM) providing the undisturbed structural context at a resolution down to the Ångstrom range, has enabled a broad range of new biological applications. Imaging rare structures or events in crowded environments, such as inside a cell, requires specific fluorescence‐based information for guiding cryo‐EM data acquisition and/or to verify the identity of the structure of interest. Furthermore, cryo‐CLEM can provide information about the arrangement of specific proteins in the wider structural context of their native nano‐environment. However, a major obstacle of cryo‐CLEM currently hindering many biological applications is the large resolution gap between cryo‐FM (typically in the range of ～400 nm) and cryo‐EM (single nanometre to the Ångstrom range). Very recently, first proof of concept experiments demonstrated the feasibility of super‐resolution cryo‐FM imaging and the correlation with cryo‐EM. This opened the door towards super‐resolution cryo‐CLEM, and thus towards direct correlation of structural details from both imaging modalities.     

The deubiquitinase Usp27x stabilizes the BH3‐only protein Bim and enhances apoptosis

Bim is a pro‐apoptotic Bcl‐2 family member of the BH3‐only protein subgroup. Expression levels of Bim determine apoptosis susceptibility in non‐malignant and in tumour cells. Bim protein expression is downregulated by proteasomal degradation following ERK‐dependent phosphorylation and ubiquitination. Here, we report the identification of a deubiquitinase, Usp27x, that binds Bim upon its ERK‐dependent phosphorylation and can upregulate its expression levels. Overexpression of Usp27x reduces ERK‐dependent Bim ubiquitination, stabilizes phosphorylated Bim, and induces apoptosis in PMA‐stimulated cells, as well as in tumour cells with a constitutively active Raf/ERK pathway. Loss of endogenous Usp27x enhances the Bim‐degrading activity of oncogenic Raf. Overexpression of Usp27x induces low levels of apoptosis in melanoma and non‐small cell lung cancer (NSCLC) cells and substantially enhances apoptosis induced in these cells by the inhibition of ERK signalling. Finally, deletion of Usp27x reduces apoptosis in NSCLC cells treated with an EGFR inhibitor. Thus, Usp27x can trigger via its proteolytic activity the deubiquitination of Bim and enhance its levels, counteracting the anti‐apoptotic effects of ERK activity, and therefore acts as a tumour suppressor.     

A stochastic model of input effectiveness during irregular gamma rhythms

Gamma-band synchronization has been linked to attention and communication between brain regions, yet the underlying dynamical mechanisms are still unclear. How does the timing and amplitude of inputs to cells that generate an endogenously noisy gamma rhythm affect the network activity and rhythm? How does such ”communication through coherence” (CTC) survive in the face of rhythm and input variability? We present a stochastic modelling approach to this question that yields a very fast computation of the effectiveness of inputs to cells involved in gamma rhythms. Our work is partly motivated by recent optogenetic experiments (Cardin et al. Nature, 459(7247), 663–667 2009) that tested the gamma phase-dependence of network responses by first stabilizing the rhythm with periodic light pulses to the interneurons (I). Our computationally efficient model E-I network of stochastic two-state neurons exhibits finite-size fluctuations. Using the Hilbert transform and Kuramoto index, we study how the stochastic phase of its gamma rhythm is entrained by external pulses. We then compute how this rhythmic inhibition controls the effectiveness of external input onto pyramidal (E) cells, and how variability shapes the window of firing opportunity. For transferring the time variations of an external input to the E cells, we find a tradeoff between the phase selectivity and depth of rate modulation. We also show that the CTC is sensitive to the jitter in the arrival times of spikes to the E cells, and to the degree of I-cell entrainment. We further find that CTC can occur even if the underlying deterministic system does not oscillate; quasicycle-type rhythms induced by the finite-size noise retain the basic CTC properties. Finally a resonance analysis confirms the relative importance of the I cell pacing for rhythm generation. Analysis of whole network behaviour, including computations of synchrony, phase and shifts in excitatory-inhibitory balance, can be further sped up by orders of magnitude using two coupled stochastic differential equations, one for each population. Our work thus yields a fast tool to numerically and analytically investigate CTC in a noisy context. It shows that CTC can be quite vulnerable to rhythm and input variability, which both decrease phase preference.     

Comparison of methods to determine the centre of resistance of teeth

In orthodontic treatment, the locations of the centre of resistance (CR) of individual teeth and the applied load system are the major determinants for the type of tooth movement achieved. Currently, CR locations have only been specified for a relatively small number of tooth specimen for research purposes. Analysing cone beam computed tomography data samples from three upper central incisors, this study explores whether the effort to establish accurate CR estimates can be reduced by (i) morphing a pre-existing simplified finite element (FE) mesh to fit to the segmented 3D tooth-bone model, and (ii) individualizing a mean CR location according to a small parameter set characterising the morphology of the tooth and its embedding. The FE morphing approach and the semi-analytical approach led to CR estimates that differ in average only 0.04 and 0.12 mm respectively from those determined by very time-consuming individual FE modelling (standard method). Both approaches may help to estimate the movement of individual teeth during orthodontic treatment and, thus, increase the therapeutic efficacy.     

Transferability of Material Composition Indicators for Residential Buildings: A Conceptual Approach Based on a German‐Japanese Comparison

Most anthropogenic material stocks and flows are associated with the building sector. Several recent studies have developed material composition indicators (MCIs) suitable for calculating material stocks and flows of the building sector using bottom‐up approaches, which hold great potential to provide information to support resource efficiency policies. A major limitation is the lack of country‐specific MCIs. This study aims to introduce a concept for a better transferability of MCI across different contexts by proposing requirements for defining MCIs and to discuss options and limits of the transferability. We take existing MCIs for residential buildings in Germany and Japan as case studies and make them comparable by applying harmonization methods. Based on that, similarities and differences are systematically identified and discussed, considering their socioeconomic, cultural, technical, and environmental factors. Our results indicate significant limitations to the transferability of MCIs for detached houses, while bigger apartment complexes show greater homogeneity despite the very different environments in which they are constructed. This indicates that while it is possible to assume foreign MCIs as plausible for large constructions, local coefficients need to be estimated for smaller single‐family homes.     

Phylogeny of spiny frogs Nanorana (Anura: Dicroglossidae) supports a Tibetan origin of a Himalayan species group

Recent advances in the understanding of the evolution of the Asian continent challenge the long‐held belief of a faunal immigration into the Himalaya. Spiny frogs of the genus Nanorana are a characteristic faunal group of the Himalaya–Tibet orogen (HTO). We examine the phylogeny of these frogs to explore alternative biogeographic scenarios for their origin in the Greater Himalaya, namely, immigration, South Tibetan origin, strict vicariance. We sequenced 150 Nanorana samples from 62 localities for three mitochondrial (1,524 bp) and three nuclear markers (2,043 bp) and complemented the data with sequence data available from GenBank. We reconstructed a gene tree, phylogenetic networks, and ancestral areas. Based on the nuDNA, we also generated a time‐calibrated species tree. The results revealed two major clades (Nanorana and Quasipaa), which originated in the Lower Miocene from eastern China and subsequently spread into the HTO (Nanorana). Five well‐supported subclades are found within Nanorana: from the East, Central, and Northwest Himalaya, the Tibetan Plateau, and the southeastern Plateau margin. The latter subclade represents the most basal group (subgenus Chaparana), the Plateau group (Nanorana) represents the sister clade to all species of the Greater Himalaya (Paa). We found no evidence for an east–west range expansion of Paa along the Himalaya, nor clear support for a strict vicariance model. Diversification in each of the three Himalayan subclades has probably occurred in distinct areas. Specimens from the NW Himalaya are placed basally relative to the highly diverse Central Himalayan group, while the lineage from the Tibetan Plateau is placed within a more terminal clade. Our data indicate a Tibetan origin of Himalayan Nanorana and support a previous hypothesis, which implies that a significant part of the Himalayan biodiversity results from primary diversification of the species groups in South Tibet before this part of the HTO was uplifted to its recent heights.     

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes

The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the following step. Yet, this strategy does not consider potential interactions between a priori distant process steps and therefore cannot guarantee for optimal overall process performance. To overcome these limitations, we established a smart approach to develop and utilize integrated process models using machine learning techniques and genetic algorithms. We evaluated the application of the data-driven models to explore potential efficiency increases and compared them to a conventional development approach for one of our development products. First, we developed a data-driven integrated process model using gradient boosting machines and Gaussian processes as machine learning techniques and a genetic algorithm as recommendation engine for two downstream unit operations, namely solubilization and refolding. Through projection of the results into our large-scale facility, we predicted a twofold increase in productivity. Second, we extended the model to a three-step model by including the capture chromatography. Here, depending on the selected baseline-process chosen for comparison, we obtained between 50% and 100% increase in productivity. These data show the successful application of machine learning techniques and optimization algorithms for downstream process development. Finally, our results highlight the importance of considering integrated process models for the whole process chain, including all unit operations.     

High resolution structure and catalysis of O-acetylserine sulfhydrylase isozyme B from Escherichia coli

The crystal structure of the dimeric O-acetylserine sulfhydrylase isozyme B from Escherichia coli (CysM), complexed with the substrate analog citrate, has been determined at 1.33 A resolution by X-ray diffraction analysis. The C1-carboxylate of citrate was bound at the carboxylate position of O-acetylserine, whereas the C6-carboxylate adopted two conformations. The activity of the enzyme and of several active center mutants was determined using an assay based on O-acetylserine and thio-nitrobenzoate (TNB). The unnatural substrate TNB was modeled into the reported structure. The substrate model and the observed mutant activities may facilitate future protein engineering attempts designed to broaden the substrate spectrum of the enzyme. A comparison of the reported structure with previously published CysM structures revealed large conformational changes. One of the crystal forms contained two dimers, each of which comprised one subunit in a closed and one in an open conformation. Although the homodimer asymmetry was most probably caused by crystal packing, it indicates that the enzyme can adopt such a state in solution, which may be relevant for the catalytic reaction.     

Towards complete sets of farnesylated and geranylgeranylated proteins

Three different prenyltransferases attach isoprenyl anchors to C-terminal motifs in substrate proteins. These lipid anchors serve for membrane attachment or protein-protein interactions in many pathways. Although well-tolerated selective prenyltransferase inhibitors are clinically available, their mode of action remains unclear since the known substrate sets of the various prenyltransferases are incomplete. The Prenylation Prediction Suite (PrePS) has been applied for large-scale predictions of prenylated proteins. To prioritize targets for experimental verification, we rank the predictions by their functional importance estimated by evolutionary conservation of the prenylation motifs within protein families. The ranked lists of predictions are accessible as PRENbase (http://mendel.imp.univie.ac.at/sat/PrePS/PRENbase) and can be queried for verification status, type of modifying enzymes (anchor type), and taxonomic distribution. Our results highlight a large group of plant metal-binding chaperones as well as several newly predicted proteins involved in ubiquitin-mediated protein degradation, enriching the known functional repertoire of prenylated proteins. Furthermore, we identify two possibly prenylated proteins in Mimivirus. The section HumanPRENbase provides complete lists of predicted prenylated human proteins-for example, the list of farnesyltransferase targets that cannot become substrates of geranylgeranyltransferase 1 and, therefore, are especially affected by farnesyltransferase inhibitors (FTIs) used in cancer and anti-parasite therapy. We report direct experimental evidence verifying the prediction of the human proteins Prickle1, Prickle2, the BRO1 domain-containing FLJ32421 (termed BROFTI), and Rab28 (short isoform) as exclusive farnesyltransferase targets. We introduce PRENbase, a database of large-scale predictions of protein prenylation substrates ranked by evolutionary conservation of the motif. Experimental evidence is presented for the selective farnesylation of targets with an evolutionary conserved modification site.